Imaging Local Diffusive Dynamics Using Diffusion Exchange Spectroscopy MRI

The movement of water between microenvironments presents a central challenge in the physics of soft matter and porous media. Diffusion exchange spectroscopy (DEXSY) is a powerful 2D nuclear magnetic resonance method for measuring such exchange, yet it is rarely used because of its long scan time requirements. Moreover, it has never been combined with magnetic resonance imaging (MRI). Using probability theory, we vastly reduce the required data, making DEXSY MRI feasible for the first time. Experiments are performed on a composite nerve tissue phantom with restricted and free water-exchanging compartments.

Figure 1

Pulse sequence and acquisition schemes. (a) The pulse sequence based on two collinear PGSEs separated by a mixing time, ${\tau }_m$. (b),(c) Schematic illustration of the data sampling strategies using (b) conventional and (c) marginal distribution constrained optimization (MADCO) approaches to obtain the 2D correlation function, $\mathcal{F}(D_1,D_2)$.

Figure 2

Schematics of geometry and microstructure of the composite white matter phantom. As ${\tau }_m$ increases, the fraction of water residing in $v_I$ during the first diffusion block (blue circles) which move to $v_E$ during the second diffusion block, and vice versa (red lines), increases as well.

Figure 3

The 1D diffusivity distribution, $F(D)$, obtained by solving Eq. (4) for the 1D case, using a 1D subset of the full DEXSY data. The integrated peaks represent equilibrium occupancies of $f_I$ and $f_E$.

Figure 4

DEXSY spectra. Top to bottom: obtained by using the entire data set ($N=6075$), and by using only $N=22$ acquisitions with MADCO. Left to right: the effect of increased ${\tau }_m$, from 15 ms to 300 ms.

Figure 5

Integrated intensities from the MADCO obtained spectra, $f_{II}$ (∘), $f_{EE}$ (△), and $f_{IE}$ (□), and their corresponding fits (–), as a function of mixing time. The 95% confidence intervals of the estimated exchange rates were [1.47, 2.28] and [1.59, 1.82] using the conventional and MADCO methods, respectively.